Lead Data Engineer

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About the Role

We are seeking a highly skilled and driven Data Engineering Lead to lead our data engineering team. The ideal candidate combines strong leadership and technical expertise with the ability to deliver results under tight timelines. You will own the end-to-end design, development, and delivery of scalable data platforms and solutions, ensuring data availability, reliability, and usability across the organization.

Key Responsibilities

• Lead, mentor, and grow a high-performing team of data engineers.
• Own the design, implementation, and optimization of data pipelines, data models, and data architectures across OLAP and operational systems.
• Drive critical data initiatives including ingestion, transformation, governance, and analytics enablement.
• Partner with product, analytics, and business teams to align data solutions with business objectives, especially in supply chain domain.
• Ensure timely and high-quality delivery of data solutions, meeting strict deadlines and performance benchmarks.
• Foster a culture of ownership, accountability, and continuous improvement within the team.
• Provide technical direction on AWS cloud-native data services including Redshift, Glue, and Quicksight.
• Oversee the creation and optimization of stored procedures, SQL scripts, Python utilities, and JSON-based workflows.
• Define and enforce standards for data modeling, metadata management, and data layer architecture.
• Collaborate with stakeholders to design data visualization and reporting solutions (Figma, QuickSight, etc.).
• Apply critical thinking to solve complex data challenges and guide the organization toward data-driven decision-making.

Required Skills & Experience

• Leadership: Proven experience managing and mentoring a team of data engineers.
• Technical Expertise:
• Strong proficiency in AWS Redshift, Glue, Quicksight.
• Advanced SQL and Stored Procedures development.
• Experience with Python, JSON, and automation scripting.
• Deep knowledge of data modeling, OLAP systems, and data layer architecture.
• Domain Knowledge: Understanding of Supply Chain systems and processes.
• Tools & Platforms: Experience with Figma (for data/UX design) and visualization frameworks.
• Soft Skills: Ownership mindset, ability to meet high-performance delivery timelines, and excellent critical thinking.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• Experience working in fast-paced environments with high-volume data systems.
• Exposure to model engineering and advanced analytics pipelines.
• Prior experience with data governance frameworks and cloud data warehousing best practices